Background:
Yoruba architecture is a courtyard-based, community-centric building form which was popular in ancient Yoruba empires. While the building form is not a common building practice in southwest Nigeria anymore, I want to explore it’s applicability to urban Lagos, which is bulging with a huge population.
Objective
To evaluate the “optimal” shape and form for the application of the courtyard structure in urban applications. Specifically considering the number of inhabitable units (function of building area), potential for ventilation and natural lighting (calculated through building perimeter) , and building cost (function of both area and perimeter).
Modeling
My goal to to model the building at a base geometry and then extruding into a solid. For the purposes of this analysis, I only modeled the building as two rectangles. In the future, I will like to do create a 3D parametric structure.
Step 1 - Generative Design Framework
- Design Variables
- Building thickness, ‘t’
- Building width
- Building length
- Evaluators
- Building cost, USD (function of area and perimeter)
- Number of Inhabitable Units (ie, ability to house max # of people)
- Building Perimeter (ie, potential for natural lighting and ventilation)
- Tradeoffs
- In a city like Lagos, the top priority is to sustainably house as many people as possible. Maximizing available living space is #1 priority.
- Natural cooling is a high priority to for many African cities, in light of global warming. It’s been predicted that most African cities will be uninhabitable in the next decade thus exacerbating the need for natural cooling.
- Then, building cost per unit will be considered, as cost is always an important factor.
Step 2 - Generative Design Study
- I did my study comparing the effects of changing the building shape (Width, height, thickness) on the three tradeoff factors mentioned above.
- I’ve outlined other aspects of the generative design study above.
Step 3 - Generative Design Study Results
Scatterplot 1
In this scatterplot, it’s clear to see that the cost per unit declines as the number of units increase. The plot shows a clear frontier! I would use this information to evaluate the location of this development. Because prices of constructing each unit are dependent on location, I will consider areas where it’s cheaper to build to remain within the efficiency of the frontier. After looking at these cost implications, I’m excited to see if there’s a relationship between the cost of building each unit, the perimeter (which I associate with the occupant comfort).
Scatterplot 2
Scatterplot 3
Unfortunately scatterplots 2 and 3 show that there is no correlation between perimeter and number of inhabitable units.
Scatterplot 4
There is a positive correlation between cost per unit and building perimeter, which is intuitive but also unfortunate. The graph shows a vague frontier. I would use this graph to see at what point the cost per unit is too significant for me as a developer. Clearly I want occupants to be comfortable, and for their comfort to be sustainable. I also want this comfort to be affordable. I would use this graph to assess the extent to which this is feasible.
